Voting Theory: Pairwise Comparison

Size: px
Start display at page:

Download "Voting Theory: Pairwise Comparison"

Transcription

1 If is removed, which candidate will win if Plurality is used? If C is removed, which candidate will win if Plurality is used? If B is removed, which candidate will win if Plurality is used?

2 Voting Method: Pairwise Comparison Definition (Method: Pairwise Comparison) For each pair of candidates, the number of voters preferring each are compared. he candidate receiving more votes (just like in Plurality) receives one point. In case of a tie, each candidate receives one-half point. After all pairs of candidates are compared, the candidate with the most points wins the election. It will often be very useful to make some chart with all the information needed. Canididate B C Points

3 Canididate B C Points

4 ie: B, C Canididate B C Points

5 ie: B, C ie: B, Canididate B C Points

6 ie: B, C ie: B, Canididate B C Points

7 ie: B, C ie: B, Canididate Points B =1 C

8 ie: B, C ie: B, Canididate Points B =1 C 0.5

9 ie: B, C ie: B, Canididate Points B =1 C =1.5

10 Example (Energy Drinks for Oregon Protesters) Ammon Bundy can t decide which energy drinks to request, so the Oregon protesters hold an election. he candidates are: Monster, Five-Hour Energy, Rockstar, and Nos. Number of Votes st Place M F N R F 2nd Place R R F N N 3rd Place F N R F R 4th Place N M M M M Which drink wins if the Pairwise Comparison method is used? Is the winner under Pairwise Comparison the same as Plurality?Borda? Plurality with Elimination?

11 Votes??? What is the maximum number of points a movie could win if the Pairwise Comparison Method is used? How many total comparisons are made to determine the winner?

12 Points Consider a Pairwise Comparison Election with n candidates. he most points a candidate can win is...n 1 points. Definition (Condorcet Candidate) In an election with n candidates, the Condorcet Candidate is the candidate thatwins n 1 points under the Pairwise Comparison method. he total number of points awarded during the Pairwise Comparison Election is given by the rule n(n 1) 2. For n = 3, there are For n = 4, there are For n = 5, there are 3(3 1) 2 = 3 otal Points. 4(4 1) 2 = 6 otal Points. 5(5 1) 2 = 10 otal Points.

13 Example (Energy Drinks for Oregon Protesters) Ammon Bundy can t decide which energy drinks to request, so the Oregon protesters hold an election. he candidates are: Monster, Five-Hour Energy, Rockstar, and Nos. Number of Votes????? 1st Place M F N R F 2nd Place R R F N N 3rd Place F N R F R 4th Place N M M M M What is the maximum number of points a movie could win if the Pairwise Comparison Method is used? How many total comparisons are made to determine the winner?

14 Voting heory: Condorcet Candidate he candidates under consideration for the Rotary club endorsement are Donald rump, ed Cruz, and Jeb Bush. Suppose we know how the Pairwise Comparison points for everyone except Bush. Name rump Cruz Bush Points 2 1? Do we know the winner if the method of Pairwise Comparison is used? Do we know how many points Bush will get?

15 Example (Energy Drinks for Oregon Protesters) Ammon Bundy can t decide which energy drinks to request, so the Oregon protesters hold an election. Suppose we only know the Pairwise Comparison points for Monster and Nos. Name Monster Five-Hour Rockstar Nos Points 2.5?? 2 Is it possible for Five-Hour Energy or Rockstar to win using Pairwise Comparison? How many combined points are shared between Five-Hour Energy and Rockstar?

Voting Handout. Election from the text, p. 47 (for use during class)

Voting Handout. Election from the text, p. 47 (for use during class) Voting Handout Election from the text, p. 47 (for use during class) 3 2 1 1 2 1 1 1 1 2 A B B B D D E B B E C C A C A A C E E C D D C A B E D C C A E E E E E B B A D B B A D D C C A D A D 1. Use the following

More information

Survey of Voting Procedures and Paradoxes

Survey of Voting Procedures and Paradoxes Survey of Voting Procedures and Paradoxes Stanford University ai.stanford.edu/ epacuit/lmh Fall, 2008 :, 1 The Voting Problem Given a (finite) set X of candidates and a (finite) set A of voters each of

More information

Chapter 1. The Mathematics of Voting

Chapter 1. The Mathematics of Voting Introduction to Contemporary Mathematics Math 112 1.1. Preference Ballots and Preference Schedules Example (The Math Club Election) The math club is electing a new president. The candidates are Alisha

More information

CMU Social choice 2: Manipulation. Teacher: Ariel Procaccia

CMU Social choice 2: Manipulation. Teacher: Ariel Procaccia CMU 15-896 Social choice 2: Manipulation Teacher: Ariel Procaccia Reminder: Voting Set of voters Set of alternatives Each voter has a ranking over the alternatives means that voter prefers to Preference

More information

Partial lecture notes THE PROBABILITY OF VIOLATING ARROW S CONDITIONS

Partial lecture notes THE PROBABILITY OF VIOLATING ARROW S CONDITIONS Partial lecture notes THE PROBABILITY OF VIOLATING ARROW S CONDITIONS 1 B. Preference Aggregation Rules 3. Anti-Plurality a. Assign zero points to a voter's last preference and one point to all other preferences.

More information

The Pairwise-Comparison Method

The Pairwise-Comparison Method The Pairwise-Comparison Method Lecture 12 Section 1.5 Robb T. Koether Hampden-Sydney College Mon, Sep 19, 2016 Robb T. Koether (Hampden-Sydney College) The Pairwise-Comparison Method Mon, Sep 19, 2016

More information

MATH 19-02: HW 5 TUFTS UNIVERSITY DEPARTMENT OF MATHEMATICS SPRING 2018

MATH 19-02: HW 5 TUFTS UNIVERSITY DEPARTMENT OF MATHEMATICS SPRING 2018 MATH 19-02: HW 5 TUFTS UNIVERSITY DEPARTMENT OF MATHEMATICS SPRING 2018 As we ve discussed, a move favorable to X is one in which some voters change their preferences so that X is raised, while the relative

More information

Spring 2016 Indiana Collegiate Mathematics Competition (ICMC) Exam

Spring 2016 Indiana Collegiate Mathematics Competition (ICMC) Exam Spring 2016 Indiana Collegiate Mathematics Competition (ICMC) Exam Mathematical Association of America Indiana Section Written by: Paul Fonstad, Justin Gash, and Stacy Hoehn (Franklin College) PROBLEM

More information

A C B D D B C A C B A D

A C B D D B C A C B A D Sample Exam 1 Name SOLUTIONS T Name e sure to use a #2 pencil. alculators are allowed, but cell phones or palm pilots are NOT acceptable. Please turn cell phones off. MULTIPLE HOIE. hoose the one alternative

More information

Lose Big, Win Big, Sum Big: An Exploration of Ranked Voting Systems

Lose Big, Win Big, Sum Big: An Exploration of Ranked Voting Systems Bard College Bard Digital Commons Senior Projects Spring 016 Bard Undergraduate Senior Projects 016 Lose Big, Win Big, Sum Big: An Exploration of Ranked Voting Systems Erin Else Stuckenbruck Bard College

More information

The Best Way to Choose a Winner

The Best Way to Choose a Winner The Best Way to Choose a Winner Vicki Powers Emory University, Atlanta, GA currently: National Science Foundation, Division of Mathematical Sciences Universität Konstanz, April 14, 2014 What is this talk

More information

Voting. José M Vidal. September 29, Abstract. The problems with voting.

Voting. José M Vidal. September 29, Abstract. The problems with voting. Voting José M Vidal Department of Computer Science and Engineering, University of South Carolina September 29, 2005 The problems with voting. Abstract The Problem The Problem The Problem Plurality The

More information

Nontransitive Dice and Arrow s Theorem

Nontransitive Dice and Arrow s Theorem Nontransitive Dice and Arrow s Theorem Undergraduates: Arthur Vartanyan, Jueyi Liu, Satvik Agarwal, Dorothy Truong Graduate Mentor: Lucas Van Meter Project Mentor: Jonah Ostroff 3 Chapter 1 Dice proofs

More information

Recap Social Choice Fun Game Voting Paradoxes Properties. Social Choice. Lecture 11. Social Choice Lecture 11, Slide 1

Recap Social Choice Fun Game Voting Paradoxes Properties. Social Choice. Lecture 11. Social Choice Lecture 11, Slide 1 Social Choice Lecture 11 Social Choice Lecture 11, Slide 1 Lecture Overview 1 Recap 2 Social Choice 3 Fun Game 4 Voting Paradoxes 5 Properties Social Choice Lecture 11, Slide 2 Formal Definition Definition

More information

Algorithmic Game Theory Introduction to Mechanism Design

Algorithmic Game Theory Introduction to Mechanism Design Algorithmic Game Theory Introduction to Mechanism Design Makis Arsenis National Technical University of Athens April 216 Makis Arsenis (NTUA) AGT April 216 1 / 41 Outline 1 Social Choice Social Choice

More information

CONNECTING PAIRWISE AND POSITIONAL ELECTION OUTCOMES

CONNECTING PAIRWISE AND POSITIONAL ELECTION OUTCOMES CONNECTING PAIRWISE AND POSITIONAL ELECTION OUTCOMES DONALD G SAARI AND TOMAS J MCINTEE INSTITUTE FOR MATHEMATICAL BEHAVIORAL SCIENCE UNIVERSITY OF CALIFORNIA, IRVINE, CA 9697-5100 Abstract General conclusions

More information

APPLIED MECHANISM DESIGN FOR SOCIAL GOOD

APPLIED MECHANISM DESIGN FOR SOCIAL GOOD APPLIED MECHANISM DESIGN FOR SOCIAL GOOD JOHN P DICKERSON Lecture #3 09/06/2016 CMSC828M Tuesdays & Thursdays 12:30pm 1:45pm REMINDER: SEND ME TOP 3 PRESENTATION PREFERENCES! I LL POST THE SCHEDULE TODAY

More information

Dr. Y. İlker TOPCU. Dr. Özgür KABAK web.itu.edu.tr/kabak/

Dr. Y. İlker TOPCU. Dr. Özgür KABAK web.itu.edu.tr/kabak/ Dr. Y. İlker TOPCU www.ilkertopcu.net www.ilkertopcu.org www.ilkertopcu.info facebook.com/yitopcu twitter.com/yitopcu instagram.com/yitopcu Dr. Özgür KABAK web.itu.edu.tr/kabak/ Decision Making? Decision

More information

Choosing Collectively Optimal Sets of Alternatives Based on the Condorcet Criterion

Choosing Collectively Optimal Sets of Alternatives Based on the Condorcet Criterion 1 / 24 Choosing Collectively Optimal Sets of Alternatives Based on the Condorcet Criterion Edith Elkind 1 Jérôme Lang 2 Abdallah Saffidine 2 1 Nanyang Technological University, Singapore 2 LAMSADE, Université

More information

Voting Paradoxes Caused by Dropping Candidates in an Election

Voting Paradoxes Caused by Dropping Candidates in an Election Voting Paradoxes Caused by Dropping Candidates in an Election Marie K. Jameson Michael Orrison, Advisor Nathan Ryan, Reader April, 7 Department of Mathematics Copyright c 7 Marie K. Jameson. The author

More information

On Social Choice Theory

On Social Choice Theory On Social Choice Theory Jan van Eijck An economist is visiting the project. The weather continues to be excellent, permitting the project members and their guest to eat their meals outside on the NIAS

More information

Introduction to Game Theory Lecture Note 2: Strategic-Form Games and Nash Equilibrium (2)

Introduction to Game Theory Lecture Note 2: Strategic-Form Games and Nash Equilibrium (2) Introduction to Game Theory Lecture Note 2: Strategic-Form Games and Nash Equilibrium (2) Haifeng Huang University of California, Merced Best response functions: example In simple games we can examine

More information

CMU Social choice: Advanced manipulation. Teachers: Avrim Blum Ariel Procaccia (this time)

CMU Social choice: Advanced manipulation. Teachers: Avrim Blum Ariel Procaccia (this time) CMU 15-896 Social choice: Advanced manipulation Teachers: Avrim Blum Ariel Procaccia (this time) Recap A Complexity-theoretic barrier to manipulation Polynomial-time greedy alg can successfully decide

More information

E PLURIBUS HUGO Out of the Many, a Hugo

E PLURIBUS HUGO Out of the Many, a Hugo v0. E PLURIBUS HUGO Out of the Many, a Hugo What does E Pluribus Hugo do? EPH is a way of tallying nominations that minimizes the effects of slates. What doesn t E Pluribus Hugo do? It doesn t change what

More information

Combining Voting Rules Together

Combining Voting Rules Together Combining Voting Rules Together Nina Narodytska and Toby Walsh and Lirong Xia 3 Abstract. We propose a simple method for combining together voting rules that performs a run-off between the different winners

More information

Analysis of Boolean Functions

Analysis of Boolean Functions Analysis of Boolean Functions Kavish Gandhi and Noah Golowich Mentor: Yufei Zhao 5th Annual MIT-PRIMES Conference Analysis of Boolean Functions, Ryan O Donnell May 16, 2015 1 Kavish Gandhi and Noah Golowich

More information

Multiple Equilibria in the Citizen-Candidate Model of Representative Democracy.

Multiple Equilibria in the Citizen-Candidate Model of Representative Democracy. Multiple Equilibria in the Citizen-Candidate Model of Representative Democracy. Amrita Dhillon and Ben Lockwood This version: March 2001 Abstract De Sinopoli and Turrini (1999) present an example to show

More information

EC3224 Autumn Lecture #03 Applications of Nash Equilibrium

EC3224 Autumn Lecture #03 Applications of Nash Equilibrium Reading EC3224 Autumn Lecture #03 Applications of Nash Equilibrium Osborne Chapter 3 By the end of this week you should be able to: apply Nash equilibrium to oligopoly games, voting games and other examples.

More information

Points-based rules respecting a pairwise-change-symmetric ordering

Points-based rules respecting a pairwise-change-symmetric ordering Points-based rules respecting a pairwise-change-symmetric ordering AMS Special Session on Voting Theory Karl-Dieter Crisman, Gordon College January 7th, 2008 A simple idea Our usual representations of

More information

MATH : FINAL EXAM INFO/LOGISTICS/ADVICE

MATH : FINAL EXAM INFO/LOGISTICS/ADVICE INFO: MATH 1300-01: FINAL EXAM INFO/LOGISTICS/ADVICE WHEN: Thursday (08/06) at 11:00am DURATION: 150 mins PROBLEM COUNT: Eleven BONUS COUNT: Two There will be three Ch13 problems, three Ch14 problems,

More information

THE PROFILE STRUCTURE FOR LUCE S CHOICE AXIOM

THE PROFILE STRUCTURE FOR LUCE S CHOICE AXIOM THE PROFILE STRUCTURE FOR LUCE S CHOICE AXIOM DONALD G SAARI Abstract A geometric approach is developed to explain several phenomena that arise with Luce s choice axiom such as where differences occur

More information

Winning probabilities in a pairwise lottery system with three alternatives

Winning probabilities in a pairwise lottery system with three alternatives Economic Theory 26, 607 617 (2005) DOI: 10.1007/s00199-004-059-8 Winning probabilities in a pairwise lottery system with three alternatives Frederick H. Chen and Jac C. Heckelman Department of Economics,

More information

Who wins the election? Polarizing outranking relations with large performance differences. Condorcet s Approach. Condorcet s method

Who wins the election? Polarizing outranking relations with large performance differences. Condorcet s Approach. Condorcet s method Who wins the election? Polarizing outranking relations with large performance differences Raymond Bisdorff Université du Luxembourg FSTC/ILAS ORBEL 26, Bruxelles, February 2012 Working hypothesis: 1. Each

More information

Algebraic Voting Theory

Algebraic Voting Theory Algebraic Voting Theory Michael Orrison Harvey Mudd College Collaborators and Sounding Boards Don Saari (UC Irvine) Anna Bargagliotti (University of Memphis) Steven Brams (NYU) Brian Lawson (Santa Monica

More information

APPLIED MECHANISM DESIGN FOR SOCIAL GOOD

APPLIED MECHANISM DESIGN FOR SOCIAL GOOD APPLIED MECHANISM DESIGN FOR SOCIAL GOOD JOHN P DICKERSON Lecture #21 11/8/2016 CMSC828M Tuesdays & Thursdays 12:30pm 1:45pm IMPOSSIBILITY RESULTS IN VOTING THEORY / SOCIAL CHOICE Thanks to: Tuomas Sandholm

More information

Mechanism Design for Bounded Agents

Mechanism Design for Bounded Agents Chapter 8 Mechanism Design for Bounded Agents Any fool can tell the truth, but it requires a man of some sense to know how to lie well. Samuel Butler Mechanism design has traditionally taken the conservative

More information

Efficient Algorithms for Hard Problems on Structured Electorates

Efficient Algorithms for Hard Problems on Structured Electorates Aspects of Computation 2017 Efficient Algorithms for Hard Problems on Structured Electorates Neeldhara Misra The standard Voting Setup and some problems that we will encounter. The standard Voting Setup

More information

Covers: Midterm Review

Covers: Midterm Review Midterm Review 1. These slides and review points found at http://math.utoledo.edu/~dgajews/1180 2. ring a photo I card: Rocket ard, river's License overs: 4.1 Graphs + uler Paths 4.2 Traveling Salesman

More information

Best reply dynamics for scoring rules

Best reply dynamics for scoring rules Best reply dynamics for scoring rules R. Reyhani M.C Wilson Department of Computer Science University of Auckland 3rd Summer workshop of CMSS, 20-22 Feb 2012 Introduction Voting game Player (voter) action

More information

Approximation algorithms and mechanism design for minimax approval voting

Approximation algorithms and mechanism design for minimax approval voting Approximation algorithms and mechanism design for minimax approval voting Ioannis Caragiannis Dimitris Kalaitzis University of Patras Vangelis Markakis Athens University of Economics and Business Outline

More information

Carolyn Anderson & YoungShil Paek (Slide contributors: Shuai Wang, Yi Zheng, Michael Culbertson, & Haiyan Li)

Carolyn Anderson & YoungShil Paek (Slide contributors: Shuai Wang, Yi Zheng, Michael Culbertson, & Haiyan Li) Carolyn Anderson & YoungShil Paek (Slide contributors: Shuai Wang, Yi Zheng, Michael Culbertson, & Haiyan Li) Department of Educational Psychology University of Illinois at Urbana-Champaign 1 Inferential

More information

Computational Aspects of Strategic Behaviour in Elections with Top-Truncated Ballots

Computational Aspects of Strategic Behaviour in Elections with Top-Truncated Ballots Computational Aspects of Strategic Behaviour in Elections with Top-Truncated Ballots by Vijay Menon A thesis presented to the University of Waterloo in fulfillment of the thesis requirement for the degree

More information

Measures of Central Tendency. Mean, Median, and Mode

Measures of Central Tendency. Mean, Median, and Mode Measures of Central Tendency Mean, Median, and Mode Population study The population under study is the 20 students in a class Imagine we ask the individuals in our population how many languages they speak.

More information

Geometry of distance-rationalization

Geometry of distance-rationalization Geometry of distance-rationalization B.Hadjibeyli M.C.Wilson Department of Computer Science, University of Auckland Benjamin Hadjibeyli (ENS Lyon) Geometry of distance-rationalization Talk CMSS 1 / 31

More information

Approval Voting: Three Examples

Approval Voting: Three Examples Approval Voting: Three Examples Francesco De Sinopoli, Bhaskar Dutta and Jean-François Laslier August, 2005 Abstract In this paper we discuss three examples of approval voting games. The first one illustrates

More information

Finite Dictatorships and Infinite Democracies

Finite Dictatorships and Infinite Democracies Finite Dictatorships and Infinite Democracies Iian B. Smythe October 20, 2015 Abstract Does there exist a reasonable method of voting that when presented with three or more alternatives avoids the undue

More information

Probabilistic Aspects of Voting

Probabilistic Aspects of Voting Probabilistic Aspects of Voting UUGANBAATAR NINJBAT DEPARTMENT OF MATHEMATICS THE NATIONAL UNIVERSITY OF MONGOLIA SAAM 2015 Outline 1. Introduction to voting theory 2. Probability and voting 2.1. Aggregating

More information

Voting and Mechanism Design

Voting and Mechanism Design José M Vidal Department of Computer Science and Engineering, University of South Carolina March 26, 2010 Abstract Voting, Mechanism design, and distributed algorithmics mechanism design. Chapter 8. Voting

More information

Condorcet Efficiency: A Preference for Indifference

Condorcet Efficiency: A Preference for Indifference Condorcet Efficiency: A Preference for Indifference William V. Gehrlein Department of Business Administration University of Delaware Newark, DE 976 USA Fabrice Valognes GREBE Department of Economics The

More information

GROUP DECISION MAKING

GROUP DECISION MAKING 1 GROUP DECISION MAKING How to join the preferences of individuals into the choice of the whole society Main subject of interest: elections = pillar of democracy Examples of voting methods Consider n alternatives,

More information

Multivariate Complexity of Swap Bribery

Multivariate Complexity of Swap Bribery Multivariate Complexity of Swap Bribery Britta Dorn 1 joint work with Ildikó Schlotter 2 1 Eberhard-Karls-Universität Tübingen/Universität Ulm, Germany 2 Budapest University of Technology and Economics,

More information

Volume 31, Issue 1. Manipulation of the Borda rule by introduction of a similar candidate. Jérôme Serais CREM UMR 6211 University of Caen

Volume 31, Issue 1. Manipulation of the Borda rule by introduction of a similar candidate. Jérôme Serais CREM UMR 6211 University of Caen Volume 31, Issue 1 Manipulation of the Borda rule by introduction of a similar candidate Jérôme Serais CREM UMR 6211 University of Caen Abstract In an election contest, a losing candidate a can manipulate

More information

Lecture: Aggregation of General Biased Signals

Lecture: Aggregation of General Biased Signals Social Networks and Social Choice Lecture Date: September 7, 2010 Lecture: Aggregation of General Biased Signals Lecturer: Elchanan Mossel Scribe: Miklos Racz So far we have talked about Condorcet s Jury

More information

Stackelberg Voting Games: Computational Aspects and Paradoxes

Stackelberg Voting Games: Computational Aspects and Paradoxes Stackelberg Voting Games: Computational Aspects and Paradoxes Lirong Xia Department of Computer Science Duke University Durham, NC 7708, USA lxia@cs.duke.edu Vincent Conitzer Department of Computer Science

More information

Social Choice and Social Networks. Aggregation of General Biased Signals (DRAFT)

Social Choice and Social Networks. Aggregation of General Biased Signals (DRAFT) Social Choice and Social Networks Aggregation of General Biased Signals (DRAFT) All rights reserved Elchanan Mossel UC Berkeley 8 Sep 2010 Extending Condorect s Jury Theorem We want to consider extensions

More information

Thema Working Paper n Université de Cergy Pontoise, France

Thema Working Paper n Université de Cergy Pontoise, France Thema Working Paper n 2010-02 Université de Cergy Pontoise, France Sincere Scoring Rules Nunez Matias May, 2010 Sincere Scoring Rules Matías Núñez May 2010 Abstract Approval Voting is shown to be the unique

More information

An NTU Cooperative Game Theoretic View of Manipulating Elections

An NTU Cooperative Game Theoretic View of Manipulating Elections An NTU Cooperative Game Theoretic View of Manipulating Elections Michael Zuckerman 1, Piotr Faliszewski 2, Vincent Conitzer 3, and Jeffrey S. Rosenschein 1 1 School of Computer Science and Engineering,

More information

Empirical Comparisons of Various Voting Methods in Bagging

Empirical Comparisons of Various Voting Methods in Bagging Empirical Comparisons of Various Voting Methods in Bagging Kelvin T. Leung, D. Stott Parker UCLA Computer Science Department Los Angeles, California 90095-1596 {kelvin,stott}@cs.ucla.edu ABSTRACT Finding

More information

Intro Prefs & Voting Electoral comp. Political Economics. Ludwig-Maximilians University Munich. Summer term / 37

Intro Prefs & Voting Electoral comp. Political Economics. Ludwig-Maximilians University Munich. Summer term / 37 1 / 37 Political Economics Ludwig-Maximilians University Munich Summer term 2010 4 / 37 Table of contents 1 Introduction(MG) 2 Preferences and voting (MG) 3 Voter turnout (MG) 4 Electoral competition (SÜ)

More information

AN ABSTRACT OF THE THESIS OF

AN ABSTRACT OF THE THESIS OF AN ABSTRACT OF THE THESIS OF Leslie M. McDonald for the degree of Master of Science in Mathematics presented on March, 205. Title: robabilities of Voting aradoxes with Three Candidates Abstract approved:

More information

Social Choice. Jan-Michael van Linthoudt

Social Choice. Jan-Michael van Linthoudt Social Choice Jan-Michael van Linthoudt Summer term 2017 Version: March 15, 2018 CONTENTS Remarks 1 0 Introduction 2 1 The Case of 2 Alternatives 3 1.1 Examples for social choice rules............................

More information

Spatial Theory in 2-space Fall 2016

Spatial Theory in 2-space Fall 2016 Spatial Theory in 2-space 17.251 Fall 2016 1 Throat-clearing Fundamental finding of unidimensional spatial model Pure majority rule: the median prevails More generally: the pivot prevails Fundamental finding

More information

Chabot College Fall Course Outline for Mathematics 47 MATHEMATICS FOR LIBERAL ARTS

Chabot College Fall Course Outline for Mathematics 47 MATHEMATICS FOR LIBERAL ARTS Chabot College Fall 2013 Course Outline for Mathematics 47 Catalog Description: MATHEMATICS FOR LIBERAL ARTS MTH 47 - Mathematics for Liberal Arts 3.00 units An introduction to a variety of mathematical

More information

UNIVERSITY OF MARYLAND Department of Economics Economics 754 Topics in Political Economy Fall 2005 Allan Drazen. Exercise Set I

UNIVERSITY OF MARYLAND Department of Economics Economics 754 Topics in Political Economy Fall 2005 Allan Drazen. Exercise Set I UNIVERSITY OF MARYLAND Department of Economics Economics 754 Topics in Political Economy Fall 005 Allan Drazen Exercise Set I The first four exercises are review of what we did in class on 8/31. The next

More information

Manipulating Stochastically Generated Single-Elimination Tournaments for Nearly All Players

Manipulating Stochastically Generated Single-Elimination Tournaments for Nearly All Players Manipulating Stochastically Generated Single-Elimination Tournaments for Nearly All Players Isabelle Stanton and Virginia Vassilevska Williams {isabelle,virgi}@eecs.berkeley.edu Computer Science Department

More information

Inequality of Representation

Inequality of Representation Inequality of Representation Hannu Nurmi Public Choice Research Centre University of Turku Institutions in Context: Inequality (HN/PCRC) Inequality of Representation June 3 9, 2013 1 / 31 The main points

More information

Repeated Downsian Electoral Competition

Repeated Downsian Electoral Competition Repeated Downsian Electoral Competition John Duggan Department of Political Science and Department of Economics University of Rochester Mark Fey Department of Political Science University of Rochester

More information

2013 IEEE International Symposium on Information Theory

2013 IEEE International Symposium on Information Theory Building Consensus via Iterative Voting Farzad Farnoud Hassanzadeh), Eitan Yaakobi, Behrouz Touri, Olgica Milenkovic, and Jehoshua Bruck Department of Electrical and Computer Engineering, University of

More information

RANK AGGREGATION AND KEMENY VOTING

RANK AGGREGATION AND KEMENY VOTING RANK AGGREGATION AND KEMENY VOTING Rolf Niedermeier FG Algorithmics and Complexity Theory Institut für Softwaretechnik und Theoretische Informatik Fakultät IV TU Berlin Germany Algorithms & Permutations,

More information

Dominating Manipulations in Voting with Partial Information

Dominating Manipulations in Voting with Partial Information Dominating Manipulations in Voting with Partial Information Vincent Conitzer Department of Computer Science Duke University Durham, NC 27708, USA conitzer@cs.duke.edu Toby Walsh NICTA and UNSW Sydney,

More information

Economics 3012 Strategic Behavior Andy McLennan October 20, 2006

Economics 3012 Strategic Behavior Andy McLennan October 20, 2006 Economics 301 Strategic Behavior Andy McLennan October 0, 006 Lecture 11 Topics Problem Set 9 Extensive Games of Imperfect Information An Example General Description Strategies and Nash Equilibrium Beliefs

More information

Chapter 12: Social Choice Theory

Chapter 12: Social Choice Theory Chapter 12: Social Choice Theory Felix Munoz-Garcia School of Economic Sciences Washington State University 1 1 Introduction In this chapter, we consider a society with I 2 individuals, each of them endowed

More information

UNIFYING VOTING THEORY FROM NAKAMURA S TO GREENBERG S THEOREMS

UNIFYING VOTING THEORY FROM NAKAMURA S TO GREENBERG S THEOREMS UNIFYING VOTING THEORY FROM NAKAMURA S TO GREENBERG S THEOREMS DONALD G SAARI Abstract Cycles, empty cores, intransitivities, and other complexities affect group decision and voting rules Approaches developed

More information

How Credible is the Prediction of a Party-Based Election?

How Credible is the Prediction of a Party-Based Election? How Credible is the Prediction of a Party-Based Election? Jiong Guo Shandong University School of Computer Science and Technology SunHua Road 1500, 250101 Jinan, China. jguo@mmci.unisaarland.de Yash Raj

More information

Introduction to Statistical Data Analysis Lecture 4: Sampling

Introduction to Statistical Data Analysis Lecture 4: Sampling Introduction to Statistical Data Analysis Lecture 4: Sampling James V. Lambers Department of Mathematics The University of Southern Mississippi James V. Lambers Statistical Data Analysis 1 / 30 Introduction

More information

Confidence Intervals for the Sample Mean

Confidence Intervals for the Sample Mean Confidence Intervals for the Sample Mean As we saw before, parameter estimators are themselves random variables. If we are going to make decisions based on these uncertain estimators, we would benefit

More information

Social Dichotomy Functions (extended abstract)

Social Dichotomy Functions (extended abstract) Social Dichotomy Functions (extended abstract) Conal Duddy, Nicolas Houy, Jérôme Lang, Ashley Piggins, and William S. Zwicker February 22, 2014 1 What is a Social Dichotomy Function? A dichotomy A = (A

More information

A New Monotonic and Clone-Independent Single-Winner Election Method

A New Monotonic and Clone-Independent Single-Winner Election Method A New Monotonic and Clone-Independent Single-Winner Election Method M Schulze Email: markus.schulze@alumni.tu-berlin.de Markus Schulze has studied mathematics and physics at the Technische Universität

More information

Political Economy of Institutions and Development: Problem Set 1. Due Date: Thursday, February 23, in class.

Political Economy of Institutions and Development: Problem Set 1. Due Date: Thursday, February 23, in class. Political Economy of Institutions and Development: 14.773 Problem Set 1 Due Date: Thursday, February 23, in class. Answer Questions 1-3. handed in. The other two questions are for practice and are not

More information

From Sentiment Analysis to Preference Aggregation

From Sentiment Analysis to Preference Aggregation From Sentiment Analysis to Preference Aggregation Umberto Grandi Department of Mathematics University of Padova 22 November 2013 [Joint work with Andrea Loreggia, Francesca Rossi and Vijay Saraswat] What

More information

Arrow s Paradox. Prerna Nadathur. January 1, 2010

Arrow s Paradox. Prerna Nadathur. January 1, 2010 Arrow s Paradox Prerna Nadathur January 1, 2010 Abstract In this paper, we examine the problem of a ranked voting system and introduce Kenneth Arrow s impossibility theorem (1951). We provide a proof sketch

More information

Mechanism Design without Money

Mechanism Design without Money Mechanism Design without Money MSc Thesis (Afstudeerscriptie) written by Sylvia Boicheva (born December 27th, 1986 in Sofia, Bulgaria) under the supervision of Prof Dr Krzysztof Apt, and submitted to the

More information

Logic and Social Choice Theory

Logic and Social Choice Theory To appear in A. Gupta and J. van Benthem (eds.), Logic and Philosophy Today, College Publications, 2011. Logic and Social Choice Theory Ulle Endriss Institute for Logic, Language and Computation University

More information

ANSWER KEY 2 GAME THEORY, ECON 395

ANSWER KEY 2 GAME THEORY, ECON 395 ANSWER KEY GAME THEORY, ECON 95 PROFESSOR A. JOSEPH GUSE (1) (Gibbons 1.6) Consider again the Cournot duopoly model with demand given by the marginal willingness to pay function: P(Q) = a Q, but this time

More information

INFLUENCE IN BLOCK VOTING SYSTEMS. September 27, 2010

INFLUENCE IN BLOCK VOTING SYSTEMS. September 27, 2010 INFLUENCE IN BLOCK VOTING SYSTEMS KENNETH HALPERN Abstract. Motivated by the examples of the electoral college and Supreme Court, we consider the behavior of binary voting systems in which votes are cast

More information

6.207/14.15: Networks Lecture 24: Decisions in Groups

6.207/14.15: Networks Lecture 24: Decisions in Groups 6.207/14.15: Networks Lecture 24: Decisions in Groups Daron Acemoglu and Asu Ozdaglar MIT December 9, 2009 1 Introduction Outline Group and collective choices Arrow s Impossibility Theorem Gibbard-Satterthwaite

More information

A Failure of Representative Democracy

A Failure of Representative Democracy A Failure of Representative Democracy Katherine Baldiga Harvard University August 30, 2011 Abstract We compare direct democracy, in which members of a population cast votes for alternatives as choice problems

More information

SPATIAL VOTING (MULTIPLE DIMENSIONS)

SPATIAL VOTING (MULTIPLE DIMENSIONS) SPATIAL VOTING (MULTIPLE DIMENSIONS) 1 Assumptions Alternatives are points in an n-dimensional space. Examples for 2D: Social Issues and Economic Issues Domestic Spending and Foreign Spending Single-peaked

More information

1. a) 6! = ! = 720 b) 9 8! = 9 ( ) 9 8! = ! = c) 5! ! 3! = ! 3! = 5 4 3!

1. a) 6! = ! = 720 b) 9 8! = 9 ( ) 9 8! = ! = c) 5! ! 3! = ! 3! = 5 4 3! Therefore, there are 9 numbers that are divisible by 5 and not by. If I add this together with the number of two-digit numbers that are divisible by two 5), I see that there are 5 two-digit numbers divisible

More information

The Impact of Dependence among Voters Preferences with Partial Indifference. William V. Gehrlein, University of Delaware

The Impact of Dependence among Voters Preferences with Partial Indifference. William V. Gehrlein, University of Delaware The Impact of Dependence among Voters Preferences with Partial Indifference Erik Friese 1, University of Rostock William V. Gehrlein, University of Delaware Dominique Lepelley, CEMOI, University of La

More information

CS 125 Section #12 (More) Probability and Randomized Algorithms 11/24/14. For random numbers X which only take on nonnegative integer values, E(X) =

CS 125 Section #12 (More) Probability and Randomized Algorithms 11/24/14. For random numbers X which only take on nonnegative integer values, E(X) = CS 125 Section #12 (More) Probability and Randomized Algorithms 11/24/14 1 Probability First, recall a couple useful facts from last time about probability: Linearity of expectation: E(aX + by ) = ae(x)

More information

Voting Systems. High School Circle II. June 4, 2017

Voting Systems. High School Circle II. June 4, 2017 Voting Systems High School Circle II June 4, 2017 Today we are going to resume what we started last week. We are going to talk more about voting systems, are we are going to being our discussion by watching

More information

The Importance of the Median Voter

The Importance of the Median Voter The Importance of the Median Voter According to Duncan Black and Anthony Downs V53.0500 NYU 1 Committee Decisions utility 0 100 x 1 x 2 x 3 x 4 x 5 V53.0500 NYU 2 Single-Peakedness Condition The preferences

More information

Exam 1 Solutions. Problem Points Score Total 145

Exam 1 Solutions. Problem Points Score Total 145 Exam Solutions Read each question carefully and answer all to the best of your ability. Show work to receive as much credit as possible. At the end of the exam, please sign the box below. Problem Points

More information

Condorcet winners on median spaces

Condorcet winners on median spaces MPRA Munich Personal RePEc Archive Condorcet winners on median spaces Berno Buechel University of Hamburg 18. April 2012 Online at http://mpra.ub.uni-muenchen.de/44625/ MPRA Paper No. 44625, posted 27.

More information

Computing with voting trees

Computing with voting trees Computing with voting trees Jennifer Iglesias Nathaniel Ince Po-Shen Loh Abstract The classical paradox of social choice theory asserts that there is no fair way to deterministically select a winner in

More information

Preference aggregation and DEA: An analysis of the methods proposed to discriminate efficient candidates

Preference aggregation and DEA: An analysis of the methods proposed to discriminate efficient candidates Preference aggregation and DEA: An analysis of the methods proposed to discriminate efficient candidates Bonifacio Llamazares, Teresa Peña Dep. de Economía Aplicada, PRESAD Research Group, Universidad

More information

Introduction to Formal Epistemology Lecture 5

Introduction to Formal Epistemology Lecture 5 Introduction to Formal Epistemology Lecture 5 Eric Pacuit and Rohit Parikh August 17, 2007 Eric Pacuit and Rohit Parikh: Introduction to Formal Epistemology, Lecture 5 1 Plan for the Course Introduction,

More information

Stat 100a: Introduction to Probability.

Stat 100a: Introduction to Probability. Stat 100a: Introduction to Probability. Outline for the day 1. Exam 2. 2. Random walks. 3. Reflection principle. 4. Ballot theorem. 5. Avoiding zero. 6. Chip proportions and induction. 7. Doubling up.

More information

Social Choice and Networks

Social Choice and Networks Social Choice and Networks Elchanan Mossel UC Berkeley All rights reserved Logistics 1 Different numbers for the course: Compsci 294 Section 063 Econ 207A Math C223A Stat 206A Room: Cory 241 Time TuTh

More information